SingleStore Helios

My main use case for SingleStore  is real-time analytics and data storage and serving for my ML workloads. It enables me to run low-latency analytics and model-driven use cases at scale, which is quite difficult for OLAP and OLTP databases alone.

One specific example of how I use SingleStore  for one of my model-driven use cases is as a data warehouse for fintech, which processes payments through TC worldwide. The integration with Azure Data Factory  occurred without complications. It helps me in an excellent way since I am very fast in obtaining the data for my dashboards. Additionally, the compression of the information is accurate.

Regarding my main use cases with SingleStore, I think it is very useful for managing information for business intelligence processes and processing. Given that the information is brought quickly, it processes correctly when loaded into the dashboard.

The best features SingleStore offers include fast data recovery and data compression by 80 percent. Having the information in sheets helps me to process the information quickly. Simplicity in T-SQL is another aspect I appreciate.

Data recovery and sheet-based processing help my team on a day-to-day basis by enabling us to handle information efficiently.

I would like to add that the data compression by 80 percent helps us in an excellent way since we are very fast in obtaining the data for our dashboards and the compression of the information is great.

SingleStore has impacted my organization positively by enabling us to run low-latency analytics and model-driven use cases at scale, which is quite difficult for OLAP and OLTP databases alone. It has been very helpful because our internal clients are happy to have the data and make data-driven decisions easily. Making decisions based on data within a two-hour delay to the transactional database is excellent since we went from twenty-four hours to two hours. I think the best contribution is decision-making with data that is close to reality.

Reducing that delay from twenty-four hours to two hours has significantly affected my team and business outcomes by increasing productivity. We have been able to serve all our customers, and they are very happy. We can deliver to them on time.

SingleStore can be improved in the aspect that the Azure  pipelines do not have many parameterization features compared to others, for example, AWS . Also, error handling needs attention. When it fails due to memory, it only indicates that but not exactly in which process it failed.

I would like to add that we need to know what the roadmap of SingleStore is.

An additional improvement needed is that the semantic layer can be better. Currently, it requires significant development experience to fine-tune queries.

I have been using SingleStore for six years and some few months.

SingleStore is stable as I find it extremely stable. I have not seen any downtime.

SingleStore's scalability is high and it can be used by any size of organization and can handle any needs of any organization.

The customer support is very proactive and responsive twenty-four hours per day, seven days per week.

Positive

I previously used a different solution, which was Oracle database.

I switched from Oracle to SingleStore because SingleStore outperforms based on my analysis with simple data sets within my organization.

I have seen a return on investment as real-time compute reduces the hassle of fine-tuning required, but it is minimal compared to other tools like Oracle or other RDBMS . Primarily, it was not client-focused. It was used for large enterprises with a significant amount of real-time data generation. The objective was to scale as data loads with high-performing query model responses.

My experience with pricing, setup cost, and licensing is that it can be a bit expensive for startups, but for my organization, the cost is affordable and cost-effective.

Before choosing SingleStore, I evaluated other options such as PostgreSQL .

My advice to others looking into using SingleStore is that it is extremely good for scenarios where large sets of data are generated in a day and the data is streamed. If you would like to run queries and analytics on such data, it would really scale and outperform TimesDB or Oracle in-memory options.

Before we wrap up, I have additional thoughts about SingleStore, stating it is a great tool that is very cost-effective. It shines as a unified solution for high OLTP and OLAP workloads. I rate this product a nine out of ten.